Overview#

This notebook gives a general overview of the features included in the dataset.

Hide imports
%load_ext autoreload
%autoreload 2
import os

import dimcat as dc
import pandas as pd
import plotly.express as px
from dimcat import filters, plotting
from IPython.display import display

import utils
RESULTS_PATH = os.path.abspath(os.path.join(utils.OUTPUT_FOLDER, "overview"))
os.makedirs(RESULTS_PATH, exist_ok=True)


def make_output_path(
    filename: str,
    extension=None,
    path=RESULTS_PATH,
) -> str:
    return utils.make_output_path(filename=filename, extension=extension, path=path)


def save_figure_as(
    fig, filename, formats=("png", "pdf"), directory=RESULTS_PATH, **kwargs
):
    if formats is not None:
        for fmt in formats:
            plotting.write_image(fig, filename, directory, format=fmt, **kwargs)
    else:
        plotting.write_image(fig, filename, directory, **kwargs)

Loading data

D = utils.get_dataset("bach_en_fr_suites", corpus_release="v2.2")
package = D.inputs.get_package()
package_info = package._package.custom
git_tag = package_info.get("git_tag")
utils.print_heading("Data and software versions")
print("J.S. Bach – English and French Suites version v2.2")
print(f"Datapackage '{package.package_name}' @ {git_tag}")
print(f"dimcat version {dc.__version__}\n")
D
Data and software versions
--------------------------

J.S. Bach – English and French Suites version v2.2
Datapackage 'bach_en_fr_suites' @ v2.2
dimcat version 3.4.0
Dataset
=======
{'inputs': {'basepath': None,
            'packages': {'bach_en_fr_suites': ["'bach_en_fr_suites.measures' (MuseScoreFacetName.MuseScoreMeasures)",
                                               "'bach_en_fr_suites.notes' (MuseScoreFacetName.MuseScoreNotes)",
                                               "'bach_en_fr_suites.expanded' (MuseScoreFacetName.MuseScoreHarmonies)",
                                               "'bach_en_fr_suites.chords' (MuseScoreFacetName.MuseScoreChords)",
                                               "'bach_en_fr_suites.metadata' (FeatureName.Metadata)"]}},
 'outputs': {'basepath': None, 'packages': {}},
 'pipeline': []}
filtered_D = filters.HasHarmonyLabelsFilter(keep_values=[True]).process(D)
all_metadata = filtered_D.get_metadata()
assert len(all_metadata) > 0, "No pieces selected for analysis."
all_metadata
TimeSig KeySig last_mc last_mn length_qb last_mc_unfolded last_mn_unfolded length_qb_unfolded volta_mcs all_notes_qb ... originalFormat wikidata musicbrainz viaf imslp pdf staff_1_instrument staff_1_ambitus staff_2_instrument staff_2_ambitus
corpus piece
bach_en_fr_suites BWV806_01_Prelude {1: '12/8'} {1: 3} 37 37 222.0 74 74 444.0 () 673.25 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/2591954a-1e63-326... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 56-84 (G#3-C6) Piano 37-76 (C#2-E5)
BWV806_02_Allemande {1: '4/4'} {1: 3} 34 32 128.0 68 64 256.0 () 498.50 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/904478b9-c079-35f... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 44-83 (G#2-B5) Piano 35-71 (B1-B4)
BWV806_03_Courante_I {1: '3/2'} {1: 3} 22 20 120.0 44 40 240.0 () 381.00 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/c54e9412-5c9a-373... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 57-83 (A3-B5) Piano 33-71 (A1-B4)
BWV806_04_Courante_II {1: '3/2'} {1: 3} 26 24 144.0 52 48 288.0 () 434.50 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/4ed9eaa4-c831-312... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 56-83 (G#3-B5) Piano 33-64 (A1-E4)
BWV806_05_Double_I {1: '3/2'} {1: 3} 26 24 144.0 52 48 288.0 () 392.50 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/4ed9eaa4-c831-312... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 61-83 (C#4-B5) Piano 33-69 (A1-A4)
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
BWV817_04_Gavotte {1: '2/2'} {1: 4} 22 20 80.0 44 40 160.0 () 226.00 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/90f3c67a-528d-36e... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 63-83 (D#4-B5) Piano 40-64 (E2-E4)
BWV817_05_Polonaise {1: '3/4'} {1: 4} 24 24 72.0 48 48 144.0 () 144.00 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/c6632594-2267-323... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 64-83 (E4-B5) Piano 37-64 (C#2-E4)
BWV817_06_Bourree {1: '2/2'} {1: 4} 44 42 168.0 88 84 336.0 () 332.00 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/d8a68c73-ef63-3f2... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 63-83 (D#4-B5) Piano 35-68 (B1-G#4)
BWV817_07_Gigue {1: '6/8'} {1: 4} 50 48 144.0 100 96 288.0 () 270.50 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/6119f93a-d4fe-371... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 59-83 (B3-B5) Piano 37-66 (C#2-F#4)
BWV817_08_Menuett {1: '3/4'} {1: 4} 24 24 72.0 48 48 144.0 () 140.00 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/a500b14f-177c-3d8... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 56-81 (G#3-A5) Piano 40-61 (E2-C#4)

89 rows × 56 columns

mean_composition_years = utils.corpus_mean_composition_years(all_metadata)
chronological_order = mean_composition_years.index.to_list()
corpus_colors = dict(zip(chronological_order, utils.CORPUS_COLOR_SCALE))
corpus_names = {
    corp: utils.get_corpus_display_name(corp) for corp in chronological_order
}
chronological_corpus_names = list(corpus_names.values())
corpus_name_colors = {
    corpus_names[corp]: color for corp, color in corpus_colors.items()
}
mean_composition_years
corpus
bach_en_fr_suites    1721.61236
Name: mean_composition_year, dtype: float64

Composition dates#

This section relies on the dataset’s metadata.

valid_composed_start = pd.to_numeric(all_metadata.composed_start, errors="coerce")
valid_composed_end = pd.to_numeric(all_metadata.composed_end, errors="coerce")
print(
    f"Composition dates range from {int(valid_composed_start.min())} {valid_composed_start.idxmin()} "
    f"to {int(valid_composed_end.max())} {valid_composed_end.idxmax()}."
)
Composition dates range from 1722 ('bach_en_fr_suites', 'BWV812_01_Allemande') to 1725 ('bach_en_fr_suites', 'BWV812_01_Allemande').

Mean composition years per corpus#

def make_summary(metadata_df):
    piece_is_annotated = metadata_df.label_count > 0
    return metadata_df[piece_is_annotated].copy()
Hide source
summary = make_summary(all_metadata)
bar_data = pd.concat(
    [
        mean_composition_years.rename("year"),
        summary.groupby(level="corpus").size().rename("pieces"),
    ],
    axis=1,
).reset_index()

N = len(summary)
fig = px.bar(
    bar_data,
    x="year",
    y="pieces",
    color="corpus",
    color_discrete_map=corpus_colors,
    title=f"Temporal coverage of the {N} annotated pieces in the Distant Listening Corpus",
)
fig.update_traces(width=5)
fig.update_layout(**utils.STD_LAYOUT)
fig.update_traces(width=5)
save_figure_as(fig, "pieces_timeline_bars")
fig.show()
summary
TimeSig KeySig last_mc last_mn length_qb last_mc_unfolded last_mn_unfolded length_qb_unfolded volta_mcs all_notes_qb ... originalFormat wikidata musicbrainz viaf imslp pdf staff_1_instrument staff_1_ambitus staff_2_instrument staff_2_ambitus
corpus piece
bach_en_fr_suites BWV806_01_Prelude {1: '12/8'} {1: 3} 37 37 222.0 74 74 444.0 () 673.25 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/2591954a-1e63-326... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 56-84 (G#3-C6) Piano 37-76 (C#2-E5)
BWV806_02_Allemande {1: '4/4'} {1: 3} 34 32 128.0 68 64 256.0 () 498.50 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/904478b9-c079-35f... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 44-83 (G#2-B5) Piano 35-71 (B1-B4)
BWV806_03_Courante_I {1: '3/2'} {1: 3} 22 20 120.0 44 40 240.0 () 381.00 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/c54e9412-5c9a-373... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 57-83 (A3-B5) Piano 33-71 (A1-B4)
BWV806_04_Courante_II {1: '3/2'} {1: 3} 26 24 144.0 52 48 288.0 () 434.50 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/4ed9eaa4-c831-312... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 56-83 (G#3-B5) Piano 33-64 (A1-E4)
BWV806_05_Double_I {1: '3/2'} {1: 3} 26 24 144.0 52 48 288.0 () 392.50 ... capx https://www.wikidata.org/wiki/Q20645323 https://musicbrainz.org/work/4ed9eaa4-c831-312... https://viaf.org/viaf/175367933/ https://imslp.org/wiki/English_Suite_No.1_in_A... https://imslp.org/wiki/Special:ReverseLookup/2094 Piano 61-83 (C#4-B5) Piano 33-69 (A1-A4)
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
BWV817_04_Gavotte {1: '2/2'} {1: 4} 22 20 80.0 44 40 160.0 () 226.00 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/90f3c67a-528d-36e... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 63-83 (D#4-B5) Piano 40-64 (E2-E4)
BWV817_05_Polonaise {1: '3/4'} {1: 4} 24 24 72.0 48 48 144.0 () 144.00 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/c6632594-2267-323... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 64-83 (E4-B5) Piano 37-64 (C#2-E4)
BWV817_06_Bourree {1: '2/2'} {1: 4} 44 42 168.0 88 84 336.0 () 332.00 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/d8a68c73-ef63-3f2... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 63-83 (D#4-B5) Piano 35-68 (B1-G#4)
BWV817_07_Gigue {1: '6/8'} {1: 4} 50 48 144.0 100 96 288.0 () 270.50 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/6119f93a-d4fe-371... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 59-83 (B3-B5) Piano 37-66 (C#2-F#4)
BWV817_08_Menuett {1: '3/4'} {1: 4} 24 24 72.0 48 48 144.0 () 140.00 ... capx https://www.wikidata.org/wiki/Q20645365 https://musicbrainz.org/work/a500b14f-177c-3d8... https://viaf.org/viaf/174207011/ https://imslp.org/wiki/French_Suite_No.6_in_E_... https://imslp.org/wiki/Special:ReverseLookup/2105 Piano 56-81 (G#3-A5) Piano 40-61 (E2-C#4)

89 rows × 56 columns

Composition years histogram#

Hide source
hist_data = summary.reset_index()
hist_data.corpus = hist_data.corpus.map(corpus_names)
fig = px.histogram(
    hist_data,
    x="composed_end",
    color="corpus",
    labels=dict(
        composed_end="decade",
        count="pieces",
    ),
    color_discrete_map=corpus_name_colors,
    title=f"Temporal coverage of the {N} annotated pieces in the Distant Listening Corpus",
)
fig.update_traces(xbins=dict(size=10))
fig.update_layout(**utils.STD_LAYOUT)
fig.update_legends(font=dict(size=16))
save_figure_as(fig, "pieces_timeline_histogram", height=1250)
fig.show()

Dimensions#

Overview#

def make_overview_table(groupby, group_name="pieces"):
    n_groups = groupby.size().rename(group_name)
    absolute_numbers = dict(
        measures=groupby.last_mn.sum(),
        length=groupby.length_qb.sum(),
        notes=groupby.n_onsets.sum(),
        labels=groupby.label_count.sum(),
    )
    absolute = pd.DataFrame.from_dict(absolute_numbers)
    absolute = pd.concat([n_groups, absolute], axis=1)
    sum_row = pd.DataFrame(absolute.sum(), columns=["sum"]).T
    absolute = pd.concat([absolute, sum_row])
    return absolute


absolute = make_overview_table(summary.groupby("workTitle"))
# print(absolute.astype(int).to_markdown())
absolute.astype(int)
pieces measures length notes labels
English Suite No. 1 10 317 1462 5587 1198
English Suite No. 2 8 422 1457 6736 1342
English Suite No. 3 8 411 1217 5346 1100
English Suite No. 4 7 292 1239 5894 1069
English Suite No. 5 7 432 1108 6634 1213
English Suite No. 6 8 411 1863 8328 1397
French Suite No. 1 6 164 619 2582 561
French Suite No. 2 6 231 608 2431 713
French Suite No. 3 7 236 746 2953 769
French Suite No. 4 7 200 676 2802 572
French Suite No. 5 7 222 795 3719 704
French Suite No. 6 8 242 816 3386 674
sum 89 3580 12607 56398 11312
def summarize_dataset(D):
    all_metadata = D.get_metadata()
    summary = make_summary(all_metadata)
    return make_overview_table(summary.groupby(level=0))


corpus_summary = summarize_dataset(D)
print(corpus_summary.astype(int).to_markdown())
|                   |   pieces |   measures |   length |   notes |   labels |
|:------------------|---------:|-----------:|---------:|--------:|---------:|
| bach_en_fr_suites |       89 |       3580 |    12607 |   56398 |    11312 |
| sum               |       89 |       3580 |    12607 |   56398 |    11312 |

Measures#

all_measures = D.get_feature("measures")
print(
    f"{len(all_measures.index)} measures over {len(all_measures.groupby(level=[0,1]))} files."
)
all_measures.head()
3683 measures over 89 files.
mc mn quarterbeats duration_qb keysig timesig act_dur mc_offset numbering_offset dont_count barline breaks repeats next volta markers jump_bwd jump_fwd play_until
corpus piece i
bach_en_fr_suites BWV806_01_Prelude 0 1 1 0 6.0 3 12/8 3/2 0 <NA> <NA> <NA> <NA> firstMeasure (2,) <NA> <NA> <NA> <NA> <NA>
1 2 2 6 6.0 3 12/8 3/2 0 <NA> <NA> <NA> <NA> <NA> (3,) <NA> <NA> <NA> <NA> <NA>
2 3 3 12 6.0 3 12/8 3/2 0 <NA> <NA> <NA> <NA> <NA> (4,) <NA> <NA> <NA> <NA> <NA>
3 4 4 18 6.0 3 12/8 3/2 0 <NA> <NA> <NA> <NA> <NA> (5,) <NA> <NA> <NA> <NA> <NA>
4 5 5 24 6.0 3 12/8 3/2 0 <NA> <NA> <NA> <NA> <NA> (6,) <NA> <NA> <NA> <NA> <NA>
all_measures.get_default_analysis().plot_grouped()

Harmony labels#

All symbols, independent of the local key (the mode of which changes their semantics).

try:
    all_annotations = D.get_feature("harmonylabels").df
except Exception:
    all_annotations = pd.DataFrame()
n_annotations = len(all_annotations.index)
includes_annotations = n_annotations > 0
if includes_annotations:
    display(all_annotations.head())
    print(f"Concatenated annotation tables contains {all_annotations.shape[0]} rows.")
    no_chord = all_annotations.root.isna()
    if no_chord.sum() > 0:
        print(
            f"{no_chord.sum()} of them are not chords. Their values are:"
            f" {all_annotations.label[no_chord].value_counts(dropna=False).to_dict()}"
        )
    all_chords = all_annotations[~no_chord].copy()
    print(
        f"Dataset contains {all_chords.shape[0]} tokens and {len(all_chords.chord.unique())} types over "
        f"{len(all_chords.groupby(level=[0,1]))} documents."
    )
    all_annotations["corpus_name"] = all_annotations.index.get_level_values(0).map(
        utils.get_corpus_display_name
    )
    all_chords["corpus_name"] = all_chords.index.get_level_values(0).map(
        utils.get_corpus_display_name
    )
else:
    print("Dataset contains no annotations.")
mc mn quarterbeats duration_qb mc_onset mn_onset timesig staff voice volta ... numeral_or_applied_to_numeral intervals_over_bass intervals_over_root scale_degrees scale_degrees_and_mode scale_degrees_major scale_degrees_minor globalkey localkey chord
corpus piece i
bach_en_fr_suites BWV806_01_Prelude 0 1 1 0 1.5 0 0 12/8 2 1 <NA> ... I (M3, P5) (M3, P5) (1, 3, 5) (1, 3, 5), major (1, 3, 5) (1, #3, 5) A I I
1 1 1 3/2 1.5 3/8 3/8 12/8 2 1 <NA> ... V (M3, P5, m7) (M3, P5, m7) (5, 7, 2, 4) (5, 7, 2, 4), major (5, 7, 2, 4) (5, #7, 2, 4) A I V7
2 1 1 3 1.5 3/4 3/4 12/8 2 1 <NA> ... I (M3, P5) (M3, P5) (1, 3, 5) (1, 3, 5), major (1, 3, 5) (1, #3, 5) A I I
3 1 1 9/2 1.5 9/8 9/8 12/8 2 1 <NA> ... V (M3, P5, m7) (M3, P5, m7) (5, 7, 2, 4) (5, 7, 2, 4), major (5, 7, 2, 4) (5, #7, 2, 4) A I V7
4 2 2 6 1.5 0 0 12/8 2 1 <NA> ... I (M3, P5) (M3, P5) (1, 3, 5) (1, 3, 5), major (1, 3, 5) (1, #3, 5) A I I

5 rows × 51 columns

Concatenated annotation tables contains 11158 rows.
Dataset contains 11158 tokens and 786 types over 89 documents.